Sort by
Refine Your Search
-
. For the working group “Past and Future Earth” (PATH) within the Research Department “Earth System Analysis”, PIK is offering an Early Career Researcher position (PhD or postdoctoral level) (m/f/d) (Position number
-
. For the working group “Past and Future Earth” (PATH) within the Research Department “Earth System Analysis”, PIK is offering an Early Career Researcher position (PhD or postdoctoral level) (m/f/d) (Position number
-
, a novel spatial discovery proteomics concept that integrates microscopic cell phenotyping with deep-learning based image analysis and global MS-based proteomics. This unique method was recently
-
23.02.2026 Application deadline : 30.04.2026 The Autonomous Systems Lab at the University of Tübingen is searching for a Postdoctoral Researcher in machine learning (m/f/d, E13 TV-L, 100%) limited
-
Python and common deep learning frameworks (PyTorch) • Excellent communication skills in English (German is a plus) • Independent, structured working style and experience in supervising students Preferred
-
multimodal vision-language models for prompt-based 3D medical image segmentation Work with large-scale clinical CT datasets and scalable deep learning pipelines Validate models in close collaboration with
-
partners. The postdoctoral researcher will also contribute to teaching in areas such as Machine Learning, NLP, AI for Education, Explainable AI, and Python-based applied seminars, supporting course
-
approaches beyond standard deep learning methods. Demonstrated experience in academic research (e. g. through publications, conference contributions or comparable scientific achievements). Very good
-
in image processing and analysis, including deep learning (e.g., CNNs) experience with correlative imaging workflows and 2D/3D registration techniques strong programming skills in Python and/or C/C
-
practical experience in machine learning, especially deep learning and its practical application in the domain of language processing and sensor analysis Solid practical experience in the field of natural